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Record W2989291952 · doi:10.2118/198700-ms

Evaluation, Implementation, and Operations of an FCD for SAGD Producer Wells

2019· article· en· W2989291952 on OpenAlexaff
Nathan J. Neeteson, Herman Heukelman, Da Zhu, Scott M. Thompson

Bibliographic record

VenueSPE Thermal Well Integrity and Design Symposium · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsAthabasca University
Fundersnot available
KeywordsChokeNozzleInflowPetroleum engineeringProcess (computing)Computer scienceWell controlField (mathematics)WellboreEngineeringMechanical engineeringGeologyElectrical engineeringOperating system

Abstract

fetched live from OpenAlex

Abstract The goal of this paper is to present the philosophies for the qualification and flow loop testing of FCD nozzles as well as the macroscopic implementation and operations of FCDs in SAGD producer wells. A quantitative methodology to evaluate FCD nozzles to choke back steam will be presented. Flow loop testing data will be shown to illustrate the qualification process. We will also discuss if sand control screens should be put on the tubing deployed inflow control devices. Some modeling and field examples will be shown. In the end, field data of the SAGD producer wells installed with the FCDs will be presented. Experience to manage and operate the wells will be shared.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.282
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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